r-cran-fpc - 2.2-13-1 main

Various methods for clustering and cluster validation. Fixed point
clustering. Linear regression clustering. Clustering by merging Gaussian
mixture components. Symmetric and asymmetric discriminant projections
for visualisation of the separation of groupings. Cluster validation
statistics for distance based clustering including corrected Rand index.
Cluster-wise cluster stability assessment. Methods for estimation of the
number of clusters: Calinski-Harabasz, Tibshirani and Walther's
prediction strength, Fang and Wang's bootstrap stability.
Gaussian/multinomial mixture fitting for mixed continuous/categorical
variables. Variable-wise statistics for cluster interpretation. DBSCAN
clustering. Interface functions for many clustering methods implemented
in R, including estimating the number of clusters with kmeans, pam and
clara. Modality diagnosis for Gaussian mixtures.